Abstract

Knowledge about the molecular mechanisms driving Alzheimer's disease (AD) is still limited. To learn more about AD biology, we performed whole transcriptome sequencing on the hippocampus of 20 AD cases and 10 age- and sex-matched cognitively healthy controls. We observed 2716 differentially expressed genes, of which 48% replicated in a second data set of 84 AD cases and 33 controls. We used an integrative network-based approach for combining transcriptomic and protein-protein interaction data to find differentially expressed gene modules that may reflect key processes in AD biology. A total of 735 differentially expressed genes were clustered into 33 modules, of which 82% replicated in a second data set, highlighting the robustness of this approach. These 27 modules were enriched for signal transduction, transport, response to stimulus, and several organic and cellular metabolic pathways. Ten modules interacted with previously described AD genes. Our study indicates that analyzing RNA-expression data based on annotated gene modules is more robust than on individual genes. We provide a comprehensive overview of the biological processes involved in AD, and the detected differentially expressed gene modules may provide a molecular basis for future research into mechanisms underlying AD.

abstract = "Knowledge about the molecular mechanisms driving Alzheimer's disease (AD) is still limited. To learn more about AD biology, we performed whole transcriptome sequencing on the hippocampus of 20 AD cases and 10 age- and sex-matched cognitively healthy controls. We observed 2716 differentially expressed genes, of which 48{\%} replicated in a second data set of 84 AD cases and 33 controls. We used an integrative network-based approach for combining transcriptomic and protein-protein interaction data to find differentially expressed gene modules that may reflect key processes in AD biology. A total of 735 differentially expressed genes were clustered into 33 modules, of which 82{\%} replicated in a second data set, highlighting the robustness of this approach. These 27 modules were enriched for signal transduction, transport, response to stimulus, and several organic and cellular metabolic pathways. Ten modules interacted with previously described AD genes. Our study indicates that analyzing RNA-expression data based on annotated gene modules is more robust than on individual genes. We provide a comprehensive overview of the biological processes involved in AD, and the detected differentially expressed gene modules may provide a molecular basis for future research into mechanisms underlying AD.",

N2 - Knowledge about the molecular mechanisms driving Alzheimer's disease (AD) is still limited. To learn more about AD biology, we performed whole transcriptome sequencing on the hippocampus of 20 AD cases and 10 age- and sex-matched cognitively healthy controls. We observed 2716 differentially expressed genes, of which 48% replicated in a second data set of 84 AD cases and 33 controls. We used an integrative network-based approach for combining transcriptomic and protein-protein interaction data to find differentially expressed gene modules that may reflect key processes in AD biology. A total of 735 differentially expressed genes were clustered into 33 modules, of which 82% replicated in a second data set, highlighting the robustness of this approach. These 27 modules were enriched for signal transduction, transport, response to stimulus, and several organic and cellular metabolic pathways. Ten modules interacted with previously described AD genes. Our study indicates that analyzing RNA-expression data based on annotated gene modules is more robust than on individual genes. We provide a comprehensive overview of the biological processes involved in AD, and the detected differentially expressed gene modules may provide a molecular basis for future research into mechanisms underlying AD.

AB - Knowledge about the molecular mechanisms driving Alzheimer's disease (AD) is still limited. To learn more about AD biology, we performed whole transcriptome sequencing on the hippocampus of 20 AD cases and 10 age- and sex-matched cognitively healthy controls. We observed 2716 differentially expressed genes, of which 48% replicated in a second data set of 84 AD cases and 33 controls. We used an integrative network-based approach for combining transcriptomic and protein-protein interaction data to find differentially expressed gene modules that may reflect key processes in AD biology. A total of 735 differentially expressed genes were clustered into 33 modules, of which 82% replicated in a second data set, highlighting the robustness of this approach. These 27 modules were enriched for signal transduction, transport, response to stimulus, and several organic and cellular metabolic pathways. Ten modules interacted with previously described AD genes. Our study indicates that analyzing RNA-expression data based on annotated gene modules is more robust than on individual genes. We provide a comprehensive overview of the biological processes involved in AD, and the detected differentially expressed gene modules may provide a molecular basis for future research into mechanisms underlying AD.